CAJ | 학술논문

在分析无刷直流电机数学模型的基础上,根据电机的物理结构建立了基于神经网络预测系统的无刷直流电机仿真模型。在仿真系统中有脉宽调制（PWM）生成模块,通过调节PWM的占空比来调节电机转速。仿真结果表明,该仿真模型输出结果与理论分析结果一致,采用神经网络控制的无刷直流电机响应快速,具有无超调量、稳态精度高的特点。
재분석무쇄직류전궤수학모형적기출상,근거전궤적물리결구건립료기우신경망락예측계통적무쇄직류전궤방진모형。재방진계통중유맥관조제（PWM）생성모괴,통과조절PWM적점공비래조절전궤전속。방진결과표명,해방진모형수출결과여이론분석결과일치,채용신경망락공제적무쇄직류전궤향응쾌속,구유무초조량、은태정도고적특점。
After the analysis of brushless DC motor＇s mathematical model,according to the physical structure of the motor,the paper built the brushless DC motor simulation model based on neural network control strategy.The simulation adopted the pulse width modulation（PWM） generation module adjusted the PWM duty cycle to regulate the motor speed,and the simulation results showed that the simulation model output would be consistent with the theoretical analysis.The applications of neural network control in brushless DC motor make the system have advantages of rapid response,without overshoot and high steady-state accuracy.